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Lidar for Turbine Control: March 1, 2005 – November 30, 2005 DE-AC36-99-GO10337

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Lidar for Turbine Control: March 1, 2005 – November 30, 2005 DE-AC36-99-GO10337 A national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy National Renewable Energy Laboratory Innovation for Our Energy Future Lidar for Turbine Control Technical Report NREL/TP-500-39154 March 1, 2005 – November 30, 2005 January 2006 M. Harris QinetiQ Limited Malvern, Worcestershire, United Kingdom M. Hand, A. Wright National Renewable Energy Laboratory Golden, Colorado NREL is operated by Midwest Research Institute ● Battelle Contract No. DE-AC36-99-GO10337 Lidar for Turbine Control Technical Report NREL/TP-500-39154 March 1, 2005 – November 30, 2005 January 2006 M. Harris QinetiQ Limited Malvern, Worcestershire, United Kingdom M. Hand, A. Wright National Renewable Energy Laboratory Golden, Colorado NREL Technical Monitor: S. Schreck Prepared under Task No. WER6.0301 and Subcontract No. YAM-5-33200-11 National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 • www.nrel.gov Operated for the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy by Midwest Research Institute • Battelle Contract No. DE-AC36-99-GO10337 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Available electronically at http://www.osti.gov/bridge Available for a processing fee to U.S. Department of Energy and its contractors, in paper, from: U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, TN 37831-0062 phone: 865.576.8401 fax: 865.576.5728 email: mailto:[email protected] Available for sale to the public, in paper, from: U.S. Department of Commerce National Technical Information Service 5285 Port Royal Road Springfield, VA 22161 phone: 800.553.6847 fax: 703.605.6900 email: [email protected] online ordering: http://www.ntis.gov/ordering.htm Printed on paper containing at least 50% wastepaper, including 20% postconsumer waste Executive Summary This work represents the first study (to our knowledge) that explores the potential of a turbine-mounted laser anemometer to enhance capabilities for wind energy production. The study combines laser anemometry (lidar) know-how from QinetiQ, Malvern, United Kingdom, with turbine design and control system expertise from the National Wind Technology Center (NWTC) at the National Renewable Energy Laboratory (NREL), Colorado, United States of America. Lidar offers a method of remote wind speed measurement. The technique was first demonstrated in the 1970s and has been used in a number of research applications. Widespread deployment of the technique has so far been hampered by the expense and complexity of lidar systems. However, the recent development of lidar systems based on optical fiber and components from the telecommunications industry promises large improvements in cost, compactness, and reliability so that it becomes viable to consider the deployment of such systems on large wind turbines for the advance detection of fluctuations in the incoming wind field. Potential advantages of this approach include increased turbine energy output and reduced turbine fatigue damage (increased lifetime); here we only explore the latter. The overall goal of the Lidar for Turbine Control study is to examine the requirements of a forward- looking lidar system, along with the associated interface to the turbine control systems. Different lidar options have been considered, including design choices such as output power, transceiver, signal processing, as well as turbine mounting and scanning options. Three configurations have been analyzed in more detail: Configuration #1 is the cheapest basic option, Configuration #2 is an intermediate option, while Configuration #3 has the greatest capability and cost. The lidar costs have been calculated on the basis of the production of 250 turbine-mounted lidar units per year with an initial run of 150 units. The final costings, which rely on assumptions and must be treated with caution, range from $45,000 to $95,000. Each of the options can accurately measure the axial component of wind speed in a timescale of order 10s of milliseconds. Hence, by scanning the beam it is possible to build a picture of the wind field in front of the turbine. A generic method for analysis of lidar output has been examined, allowing a modelling representation of the lidar input to the control system. This involves derivation of the line-of-sight component of wind speed for each point interrogated, followed by a weighted summation of these components to derive the lidar spectrum for a given geometry. Full-field simulated turbulent wind fields are created using TurbSim, a code developed by NREL that generates a binary data file containing u, v, and w velocity components at evenly spaced grid points in a plane. A module was then added to the FAST aeroelastic wind turbine simulation code to simulate a lidar device. The current study explores the inclusion of forward-looking lidar as input to a control algorithm to mitigate fatigue loads at the blade root in above-rated wind speed conditions. The use of forward-looking lidar could enhance a wide range of control systems in a number of regimes; however, the scope of this study is restricted to examination of speed regulation and load mitigation in Control Region 3 for the NWTC’s CART (Controls Advanced Research Turbine). This is a 2-bladed, teetered-hub, variable-speed machine, but a rigid hub was simulated in this study. The turbine is rated at 600 kW; it has a 43-m rotor diameter and a 36-m hub height. At rated power, the turbine rotates at 41.7 rpm. It is outfitted with servo-electric motors capable of pitching the blades independently, precisely, and quickly. This wind turbine was selected for this simulation study because a number of sophisticated control algorithms have been tested on it. The results indicate that damage equivalent flap loads can be reduced by approximately 10% under turbulent wind inflow conditions when lidar signals are included as measurements to the controller. Studies such as this could eventually feed into an estimate of the reduction in cost of energy (COE) that would result from the widespread deployment of turbine-mounted lidar. iii As a first study in the field of turbine-mounted lidar, this work has identified a number of potential areas for future research, including further modelling investigations to examine some of the other regimes identified. Controllers that include lidar-based wind measurement inputs must be specifically designed for each of the operating regimes. Eventually the modelling studies must extend to larger-scale turbines in order to arrive at a realistic estimate for the reduction in the COE. Current industry standard machines are rated at 1.5 MW with rotor diameters on the order of 80 m, but many companies are developing even larger turbines. It would also be highly desirable to conduct experiments on turbine-mounted lidar to verify the results of the modelling work. Any scheme would ideally retain enough flexibility to explore different scan patterns and focus range options. These lidar experiments will also provide the capability for a wider range of investigations, including power curve measurement and turbine wake and shadowing studies. Also, field testing is required to address concerns regarding the true correlation between upwind flow measurements and the turbine response. These differences cannot be simulated with current simulation capabilities. iv Table of Contents 1 Introduction...............................................................................................................................1 2 Overview of Lidar Techniques .................................................................................................2 2.1 Basic Principles of CLR............................................................................................2 2.2 Continuous Wave (CW) Lidar ..................................................................................4 2.3 Pulsed Lidar ..............................................................................................................5 2.4 Choice of Laser Wavelength.....................................................................................5 2.5 The QinetiQ ZephIR Lidar System...........................................................................6 3 Options for Turbine-Mounted Lidar.........................................................................................9 3.1 Previous Work ..........................................................................................................9 3.2 Consideration of Turbine-Mounted Lidar Options .................................................10 3.2.1 Environmental Conditions ................................................................................10
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